Can Llama 4 Scout 17B 16E run on H100 NVL 188GB?
YES — Runs Great
Llama 4 Scout 17B 16E needs ~89.4 GB VRAM. H100 NVL 188GB has 188.0 GB. With Q4_K_M quantization, expect ~242 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
241.6 tok/s
TTFT
801 ms
Safe context
554K
Memory
89.4 GB / 188.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 223.7 tok/s | 472 ms | 554K |
| Coding | A | Runs well | 241.6 tok/s | 801 ms | 554K |
| Agentic Coding | A | Runs well | 241.6 tok/s | 1166 ms | 554K |
| Reasoning | A | Runs well | 241.6 tok/s | 947 ms | 554K |
| RAG | A | Runs well | 241.6 tok/s | 1457 ms | 554K |
Quantization options
How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on H100 NVL 188GB (188.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 42.5 GB | Low | B68 |
Q3_K_S | 3 | 53.4 GB | Low | B70 |
NVFP4 | 4 | 61.0 GB | Medium | A71 |
Q4_K_M | 4 | 66.5 GB | Medium | A71 |
Q5_K_M | 5 | 78.5 GB | High | A73 |
Q6_K | 6 | 89.4 GB | High | A74 |
Q8_0Best for your GPU | 8 | 116.6 GB | Very High | A76 |
F16 | 16 | 223.5 GB | Maximum | F0 |
Get started
Copy-paste commands to run Llama 4 Scout 17B 16E on your machine.
Run
lms load Llama-4-Scout-17B-16E-Instruct && lms server startYour hardware
More models your H100 NVL 188GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 91.6 tok/s | ||
| 122B | S | 254 tok/s | ||
| 284B | S | 136.1 tok/s | ||
| 119B | S | 275.4 tok/s | ||
| 117B | S | 96.3 tok/s |
Frequently asked questions
Can H100 NVL 188GB run Llama 4 Scout 17B 16E?
Yes, H100 NVL 188GB can run Llama 4 Scout 17B 16E with a A grade (Runs well). Expected decode speed: 241.6 tok/s.
How much VRAM does Llama 4 Scout 17B 16E need?
Llama 4 Scout 17B 16E (109B parameters) requires approximately 89.4 GB of memory with Q4_K_M quantization.
What is the best quantization for Llama 4 Scout 17B 16E?
The recommended quantization for Llama 4 Scout 17B 16E is Q4_K_M, which balances quality and memory efficiency.
What speed will Llama 4 Scout 17B 16E run at on H100 NVL 188GB?
On H100 NVL 188GB, Llama 4 Scout 17B 16E achieves approximately 241.6 tokens per second decode speed with a time-to-first-token of 801ms using Q4_K_M quantization.
Can H100 NVL 188GB run Llama 4 Scout 17B 16E for coding?
For coding workloads, Llama 4 Scout 17B 16E on H100 NVL 188GB receives a A grade with 241.6 tok/s and 554K context.
What context window can Llama 4 Scout 17B 16E use on H100 NVL 188GB?
On H100 NVL 188GB, Llama 4 Scout 17B 16E can safely use up to 554K tokens of context. The model's official context limit is 10.5M, but available memory constrains the safe maximum.
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